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list_pipeline_traces

Retrieve paginated summaries of Haystack pipeline runs, including query ID, status, and duration, to quickly find slow or failed queries.

Instructions

Lists Haystack pipeline run trace summaries for a specific pipeline.

Returns one lightweight summary per query run — query_id, query text, status, timing (duration_s, created_at), and failure details if the run failed. Summaries do not include spans or logs. Use this to browse runs, find slow or failed queries, then pass a query_id to get_pipeline_trace for the full execution trace (spans with component input/output and logs), or to get_pipeline_trace_logs for just the logs.

This tool resolves the pipeline and workspace IDs automatically and calls the v2 traces endpoint under the hood.

Use the after parameter with next_cursor from the response to fetch the next page. :param pipeline_name: Name of the pipeline to retrieve traces for. :param limit: Maximum number of trace entries to return per page (default 10). :param after: ISO-8601 timestamp cursor from next_cursor on the previous response. :param query_filter: An OData filter expression to narrow down results. Supported fields: query, client_source_path, pipeline_version_id, answer, api_key, created_at, created_by, tags/tag_id, feedbacks, feedbacks/score, feedbacks/comment, feedbacks/bookmarked, session_id, search_session_id, feedbacks/result_id, request/filters, request/params, duration, labels, status, note. Example: "status eq 'failed'" or "created_at ge 2024-01-01T00:00:00Z". :param sort_field: Field to sort results by. One of: created_at, query, duration, feedbacks/score. Defaults to created_at. :param sort_order: Sort direction — ASC (oldest first) or DESC (newest first). Defaults to DESC. :returns: Paginated list of pipeline trace summaries or an error message.

The output is automatically stored and can be referenced in other functions. Returns a formatted preview with an object ID (e.g., @obj_123). Use the object store tools in combination with the object ID to view nested properties of the object. Use the returned object ID to pass this result to other functions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
afterNo
limitNo
sort_fieldNocreated_at
sort_orderNoDESC
query_filterNo
pipeline_nameYes
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries full burden. It discloses that the tool resolves pipeline and workspace IDs automatically, calls v2 endpoint, does not include spans/logs, and that output is automatically stored with an object ID. Almost covers all behavioral aspects; could be slightly more explicit about idempotency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Description is well-structured with clear paragraphs: overview, usage, technical details, pagination, then param list. Though slightly verbose, every sentence adds value. Front-loaded with purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 6 parameters, 0% schema coverage, no output schema, and no annotations, the description thoroughly covers return value (fields), pagination, param details, and integration with other tools. It is complete for an agent to use correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so description must compensate. It provides detailed documentation for all 6 parameters, including defaults, examples for query_filter, and enum values for sort_field and sort_order. This fully adds meaning beyond the raw schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it lists Haystack pipeline run trace summaries for a specific pipeline. It distinguishes itself from siblings get_pipeline_trace and get_pipeline_trace_logs by noting that summaries do not include spans or logs, making the purpose precise.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicit guidance on when to use this tool: 'browse runs, find slow or failed queries' and when not: for full execution trace or logs, use get_pipeline_trace or get_pipeline_trace_logs. Also explains pagination with after parameter.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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